A highway system development involves huge irreversible investments, and requires rigorous modeling and analysis before the implementation decision is made. This decision-making process is embedded with multiple uncertainties due to changes in political, social, and environmental contexts. In this paper, we present a multistage stochastic model for decision making in highway development, operation, expansion, and rehabilitation. This model accounts for the evolution of three uncertainties, namely, traffic demand, land price, and highway deterioration, as well as their interdependence. Real options in both development and operation phases of a highway are also incorporated in the model. A solution algorithm based on the Monte Carlo simulation and least-squares regression is developed. Numerical results show that the proposed model and solution algorithm are promising. This model makes a radical and conceptual step towards optimal decision making in highway engineering, which achieves decision-making optimality that is generally not well defined in traditional policy-based approaches for highway planning.
This paper discusses decision making of project funding allocation under uncertain project costs. Because project costs are uncertain and funding allocations may not necessarily match the costs required, each project is inherently subject to a cost overrun risk (COR). In this paper, a model is proposed in which project cost is treated as a factor with a probability density function. The decision maker then allocates the total funding to the projects while minimizing a weighted sum of mean and variance of the COR of the project portfolio. Some properties of project COR are derived and interpreted. Optimal funding allocation, in relationship to factors such as various project sizes and riskiness, project interdependency, and the decision maker's risk preference, is analyzed. The proposed funding allocation model can be integrated with project selection decision-making and provides a basis for more effective project control.
Long term financing to infrastructure and mobilization of private long term capital has been recognized as a key agenda in advancing the global economic development. There are several barriers in infrastructure financing and big gaps between expectation and reality. A highly pronounced barrier is the lacking of capacity of investors to price risks in a structured manner. This paper has discussed component-based infrastructure valuation analysis and modeling blocks. The component-based valuation mechanism is very useful for issuers and investors to categorize, analyze and price specific risks transparently and can provide a basis for structuring the risks on an ex-ante basis so as to make project investments suitable for investors of different risk preference.
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